Search Results (302)

This paper presents the design, development, and evaluation of a proof-of-concept arm swing facilitator device (ASFD) to promote proper arm swing during gait training. Although coordinated arm swing plays a critical role in human locomotion and neurorehabilitation, few wearable systems have been developed to integrate it into gait training. The ASFD was designed to test the feasibility of generating torque at the shoulder joint to initiate arm flexion–extension motion while allowing other shoulder degrees of freedom to move freely. The device induced cyclic arm motion at 1 Hz, producing sufficient torque while maintaining ergonomic criteria, such as a large workspace and back-mounted actuation to minimize arm load. The system incorporated a double-parallelogram mechanism to expand the workspace and a two-stage pulley–belt transmission to amplify torque. Testing showed that the ASFD produced up to 15 N·m and 11 N·m torques in static and dynamic load tests, respectively. Kinematic and experimental analyses confirmed sufficient motion freedom, except for some constraints in rotation. Human subject experiment demonstrated that the ASFD successfully induced arm swing within the 0.8–1.2 Hz frequency range and torques below 11 N·m. The ASFD met its design objectives, establishing a foundation for future development aimed at gait rehabilitation applications. Full article

Unmanned underwater vehicles (UUVs) capable of agile, high-speed maneuvering in complex environments require propulsion systems that can dynamically modulate three-dimensional forces. The California sea lion (Zalophus californianus) provides an exceptional biological model, using its foreflippers to achieve rapid turns and powerful propulsion. However, the specific kinematic mechanisms that govern instantaneous force generation from its powerful foreflippers remain poorly quantified. This study experimentally characterizes the time-varying thrust and lift produced by a bio-robotic sea lion foreflipper to determine how flipper twist, sweep, and phase overlap modulate propulsive forces. A three-degree-of-freedom bio-robotic flipper with a simplified, low-aspect-ratio planform and single compliant hinge was tested in a circulating flow tank, executing parameterized power and paddle strokes in both isolated and combined-phase trials. The time-resolved force data reveal that the propulsive stroke functions as a tunable hybrid system. The power phase acts as a force-vectoring mechanism, where the flipper’s twist angle reorients the resultant vector: thrust is maximized in a broad, robust range peaking near 45°, while lift increases monotonically to 90°. The paddle phase operates as a flow-insensitive, geometrically driven thruster, where twist angle (0° optimal) regulates thrust by altering the presented surface area. In the full stroke, a temporal-phase overlap governs thrust augmentation, while the power-phase twist provides robust steering control. Within the tested inertial flow regime (Re ≈ 10⁴–10⁵), this control map is highly consistent with propulsion dominated by geometric momentum redirection and impulse timing, rather than circulation-based lift. These findings establish a practical, experimentally derived control map linking kinematic inputs to propulsive force vectors, providing a foundation for the design and control of agile, bio-inspired underwater vehicles. Full article

The development of collagen-based composite materials for bone tissue engineering requires a comprehensive understanding of their rheological and structural behavior to ensure processability and functional stability. This study investigates the viscoelastic and morphological properties of nanocomposite slurries composed of hydroxyapatite (HA) nanoparticles dispersed in acetic acid solutions of bovine or fish-derived collagen peptides. Frequency and strain sweep tests revealed solid-like behavior and shear-thinning characteristics consistent with printable bioinks. Both formulations yield stresses between 0.7 and 1.5 kPa, values comparable to those reported for 3D-printable HA composites. Over ten days of aging, fish-based formulations retained higher viscosity and modulus, indicating improved temporal stability relative to bovine-based ones. Drop-casting tests confirmed the formation of homogeneous, highly opalescent films, with surface profilometry showing lower waviness for the fish-derived blend, suggesting enhanced microstructural uniformity. These results demonstrate that acetic acid-mediated collagen–HA interactions generate stable, high-fidelity slurries suitable for additive manufacturing applications. The superior rheological properties of fish collagen formulations highlight the influence of peptide source on network evolution, offering valuable insight for optimizing collagen–ceramic composites in regenerative and biomedical applications. Full article

Cactaceae are plants equipped with spines and adapted to extremely arid environments. In particular, Echinocactus grusonii spines are almost cylindrical structures, which may occasionally present an enlargement of their proximal cross sectional area. In this work, the spines of Echinocactus grusonii were explored as a possible source of biomimetic inspiration for the design and the implantation strategies of self-inserting intraneural interfaces. More specifically, the elastic stability of spines was theoretically studied for structures able to puncture the surface of an external object, as well as for structures unable to pierce it. The biomimicry of Echinocactus grusonii spines suggested an improved insertion strategy for self-inserting intraneural interfaces together with structural changes able to increase their elastic stability. The theoretical approach provided in this work was able to predict an increase of the first buckling threshold up to 39% for not puncturing self-inserting neural interfaces, and up to 59% for puncturing ones. Full article

Chitosan films obtained by solution casting were investigated by broadband dielectric spectroscopy (BDS) to explore both their glass transition and the effects of thermal annealing on molecular dynamics, deriving from residual water content as well as from cold crystallization. Glass transition at low temperatures could be evidenced in as-produced as well as thermally annealed films, where non-Arrhenian dielectric relaxation processes, consistent with a structural (α) relaxation, could be detected. The process detected at low temperatures could reflect the dynamics of residual water slaved by the polymer matrix. Secondary (β) relaxations, along with a slow process ascribed to interfacial polarization at the amorphous/crystalline interfaces, were concurrently detected. In most cases, a further Arrhenian process at intermediate temperatures (α_c) was present, also indicative of crystallization. Notably, the α processes, due to the primary relaxation of the polymer matrix plasticized by water, could be discriminated from other processes, present in the same frequency range, thanks to improvements in the dielectric fitting strategy. All relaxation processes showed the expected dependence on T_a. The more accurate exploration of the glass transition for chitosan helps to better rationalize its crystallization behavior, in view of an optimized application of this biopolymer. Full article

The origin of life initiated an evolutionary continuum yielding biologically optimized systems capable of operating under extreme environmental constraints. Biomimetics, defined as the systematic abstraction and transfer of biological principles into engineering domains, has become a strategic design paradigm for addressing the multifactorial challenges of space systems. This study introduces two core contributions to formally establish the discipline of Aerospace Bionic Robotics (ABR): First, it elucidates the relevance of biologically derived functionalities such as autonomy, adaptability, and multifunctionality to enhance the efficiency of space robotic platforms operating in microgravity environments. Second, it proposed the BEAM-D (Biomimetic Engineering and Aerospace Mechatronics Design), a standard for the development of Aerospace Bionic Robotics. By integrating biological abstraction levels (morphological, functional, and behavioral) with engineering protocols including ISO, VDI, and NASA’s TRL, BEAM-D enables a structured design pathway encompassing subsystem specification, cyber–physical integration, in situ testing, and full-scale mission deployment. It is implemented through a modular BEAM-DX framework and reinforced by iterative BIOX design steps. This study thus establishes formalized bio-inspired design tools for advanced orbital and planetary robotic systems capable of sustained autonomous operations in deep space exploration scenarios. Full article

Robot-assisted radical prostatectomy (RARP) has become the most prevalent treatment for patients with organ-confined prostate cancer. Despite superior outcomes, suboptimal vesicourethral anastomosis (VUA) may lead to serious complications, including urinary leakage, prolonged catheterization, and extended hospitalization. A precise localization of both the surgical needle and the surrounding vesical and urethral tissues to coadapt is needed for fine-grained assessment of this task. Nonetheless, the identification of anatomical structures from endoscopic videos is difficult due to tissue distortions, changes in brightness, and instrument interferences. In this paper, we propose and compare two Deep Learning (DL) pipelines for the automatic segmentation of the mucosal layers and the suturing needle in real RARP videos by exploiting different architectures and training strategies. To train the models, we introduce a novel, annotated dataset collected from four VUA procedures. Experimental results show that the nnU-Net 2D model achieved the highest class-specific metrics, with a Dice Score of 0.663 for the mucosa class and 0.866 for the needle class, outperforming both transformer-based and baseline convolutional approaches on external validation video sequences. This work paves the way for computer-assisted tools that can objectively evaluate surgical performance during the critical phase of suturing tasks. Full article

Decoding motor imagery (MI) of lower-limb movements from electroencephalography (EEG) signals remains a challenge due to the involvement of deep cortical regions, limiting the applicability of Brain–Computer Interfaces (BCIs). This study proposes a novel protocol that combines passive pedaling (PP) as sensory priming with MI at different speeds (30, 45, and 60 rpm) to improve EEG-based classification. Ten healthy participants performed PP followed by MI tasks while EEG data were recorded. An increase in spectral relative power around Cz associated with both PP and MI was observed, varying with speed and suggesting that PP may enhance cortical engagement during MI. Furthermore, our classification strategy, based on Convolutional Neural Networks (CNNs), achieved an accuracy of 0.87–0.89 across four classes (three speeds and rest). This performance was also compared with the standard Common Spatial Patterns (CSP) and Linear Discriminant Analysis (LDA), which achieved an accuracy of 0.67–0.76. These results demonstrate the feasibility of multiclass decoding of imagined pedaling velocities and lay the groundwork for speed-adaptive BCIs, supporting future personalized and user-centered neurorehabilitation interventions. Full article

Optimal upper limb (UpL) function is essential for performing daily activities; however, children with unilateral spastic cerebral palsy (USCP) often experience impairments in UpL function, which can impact their quality of life or independence. While UpL motor impairments are a primary concern, non-motor functions, such as cognition, attention, and visual function, commonly impaired in USCP, may also play a role in UpL performance. Nevertheless, these non-motor functions are often not considered in evaluation protocols that focus on the UpL. Moreover, clinical evaluation is typically conducted in structured and controlled settings and may not accurately reflect the child’s abilities in daily life. Non-invasive, novel technologies are a promising solution for filling this gap, by providing additional quantitative and ecologically valid information to clinicians. In this context, this overview aims (i) to present the most frequently used tools for a holistic evaluation in children with USCP, ensuring a thorough understanding of the UpL function, and (ii) to report the evidence of how novel, non-invasive technologies can enhance clinical evaluation in daily life, enabling a more comprehensive evaluation. This work could set a basis for multidimensional evaluation protocols for UpL function in USCP, providing a different approach to the current standards. Full article

Biorobotics leverages the principles of natural locomotion to enhance the mobility of bioinspired aquatic robots. Among various swimming modes, anguilliform locomotion is particularly recognized as an energy-efficient mode incorporating complex multiphysics. Due to whole-body undulation, the determination of the anguilliform swimmer’s direction is not trivial. Furthermore, the neuromuscular mechanism that controls straight swimming is not fully understood. This study investigates the challenge of predicting and controling the gross motion trajectory of a soft robot that utilizes anguilliform swimming. The robot consists of a six-segment continuous body, where each segment is actuated with pneumatic artificial muscles. A mode extraction technique based on dynamic mode decomposition (DMD) is proposed to identify the robot’s future state. Using the complex-variable delay embedding (CDE) technique, the CDE DMD algorithm is developed to predict the robot trajectory trend. To vary the robot direction, a hypothesis that asymmetric sidewise actuation results in slightly different fluid velocities between the left and right sides of the robot was investigated using COMSOL Multiphysics^® 6.2. The simulation results demonstrate the CDE DMD’s ability to predict gross motion across various scenarios. Furthermore, integrating the prediction model with the asymmetric actuation rule provides a control strategy for directional stability of the robot. Simulations of the closed-loop system with non-zero initial pose (step response) indicate the performance in maintaining straight-line swimming with approximately a 60s settling time. Full article

Resistive stretching sensors are currently used in healthcare robotics due to their ability to vary electrical resistance when subjected to mechanical strain. However, commercial sensors often lack the softness required for integration into soft structures. This study presents a detailed methodology to characterize fabric-based resistive stretching sensors, focusing on both static and dynamic performance, for application in a smart vascular simulator for surgical training. Five sensors, called #1–#5, were developed using conductive fabrics integrated into soft silicone. Stability and fatigue tests were performed to evaluate their behavior. The surface structure and fiber distribution were analyzed using digital microscopy and scanning electron microscopy, while element analysis was performed via Energy-Dispersive X-ray Spectroscopy. Sensors #1 and #3 are the most stable with a low relative standard deviation and good sensitivity at low strains. Sensor #3 showed the lowest hysteresis, while sensor #1 had the widest operating range (0–30% strain). Although all sensors showed non-monotonic behavior across 0–100% strain, deeper investigation suggested that the sensor response depends on the configuration of conductive paths within and between fabric layers. Soft fabric-based resistive sensors represent a promising technical solution for physical simulators for surgical training. Full article

This study evaluates the effects of hypergravity (HG) on a neurodegenerative model in vitro, looking at how HG influences Tau protein aggregation in Mouse Hippocampal Neuronal Cells (HT22) induced by neurofibrillary tangle seeds. Overall, 50× g significantly, synergistically, reduced the Tau aggregate Area when combined with ERK-inhibitor PD-0325901, correlating with decreased phosphorylation at critical residues pS262 and pS396. These findings suggest HG treatments may help mitigate cytoskeletal damage linked to Tau aggregation. Full article

Biological systems can adaptively navigate multi-terrain environments via morphological and behavioral flexibility. While robotic systems increasingly achieve locomotion versatility in one or two domains, integrating terrestrial, aquatic, and aerial mobility into a single platform remains an engineering challenge. This work tackles this by introducing a bipedal robot equipped with a reconfigurable locomotion framework, enabling seven adaptive policies: (1) thrust-assisted jumping, (2) legged crawling, (3) balanced wheeling, (4) tricycle wheeling, (5) paddling-based swimming, (6) air-propelled drifting, and (7) quadcopter flight. Field experiments and indoor statistical tests validated these capabilities. The robot achieved a 3.7-m vertical jump via thrust forces counteracting gravitational forces. A unified paddling mechanism enabled seamless transitions between crawling and swimming modes, allowing amphibious mobility in transitional environments such as riverbanks. The crawling mode demonstrated the traversal on uneven substrates (e.g., medium-density grassland, soft sand, and cobblestones) while generating sufficient push forces for object transport. In contrast, wheeling modes prioritize speed and efficiency on flat terrain. The aquatic locomotion was validated through trials in static water, an open river, and a narrow stream. The flight mode was investigated with the assistance of the jumping mechanism. By bridging terrestrial, aquatic, and aerial locomotion, this platform may have the potential for search-and-rescue and environmental monitoring applications. Full article

This article explores the transformative advances in soft machines, where biology, materials science, and engineering have converged. We discuss the remarkable adaptability and versatility of soft machines, whose designs draw inspiration from nature’s elegant solutions. From the intricate movements of octopus tentacles to the resilience of an elephant’s trunk, nature provides a wealth of inspiration for designing robots capable of navigating complex environments with grace and efficiency. Central to this advancement is the ongoing research into bioinspired materials, which serve as the building blocks for creating soft machines with lifelike behaviors and adaptive capabilities. By fostering collaboration and innovation, we can unlock new possibilities in soft machines, shaping a future where robots seamlessly integrate into and interact with the natural world, offering solutions to humanity’s most pressing challenges. Full article